Triple

T29475979
Position Surface form Disambiguated ID Type / Status
Subject Ordet E747647 entity
Predicate castMember P1668 FINISHED
Object Emil Hass Christensen
Emil Hass Christensen was a Danish actor best known for his role in Carl Theodor Dreyer’s classic film "Ordet."
E1877591 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Emil Hass Christensen | Statement: [Ordet, castMember, Emil Hass Christensen]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Emil Hass Christensen
Triple: [Ordet, castMember, Emil Hass Christensen]
Generated description
Emil Hass Christensen was a Danish actor best known for his role in Carl Theodor Dreyer’s classic film "Ordet."

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f0bd42cf308190bb01b20bc5b7c2d0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66bd4bb388190b1a797e7b3a25098 completed May 2, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26614e05e08190b508d21235620a45 completed June 8, 2026, 6:29 a.m.
NEDg Description generation batch_6a2673dceffc8190b6d908e2f64a9641 completed June 8, 2026, 7:48 a.m.
NED2 Entity disambiguation (via description) batch_6a267473df5c8190abe85ab2c4f64520 completed June 8, 2026, 7:51 a.m.
Created at: April 28, 2026, 4 p.m.